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Predictors of Fatal and Non-Fatal Overdose Following Prescription of Opioids for Chronic Pain: A Systematic Review and Meta-Analysis of Observational Studies

40 Pages Posted: 3 Mar 2023

See all articles by Li Wang

Li Wang

McMaster University - Department of Anesthesia

Patrick J. Hong

University of Toronto - Department of Anesthesiology and Pain Medicine

Wenjun Jiang

McMaster University - Faculty of Health Sciences

Yasir Rehman

McMaster University - Michael G. DeGroote Institute for Pain Research and Care

Brian Y. Hong

University of Toronto - Division of Plastic Surgery

Rachel J. Couban

McMaster University - Michael G. DeGroote Institute for Pain Research and Care

Chunming Wang

Guangdong Academy of Sciences (GDAS) - Guangdong Science and Technology Library, and Institute of Information

Corey Hayes

University of Arkansas for Medical Sciences - Bioinformatics Program

David N. Juurlink

Queen's University - Institute for Clinical Evaluative Sciences

Jason W. Busse

McMaster University - Department of Anesthesia

More...

Abstract

Background: Factors associated with opioid overdose when prescribed for chronic pain are unclear.  We aimed to explore predictors of opioid overdose after prescription for chronic pain.

Methods: We searched MEDLINE, EMBASE, CINAHL, PsycINFO and Web of Science up to October 30, 2022, for observational studies that explored predictors of opioid overdose following prescription for chronic pain.  Paired reviewers independently extracted data, assessed risk of bias and certainty of evidence. We performed random-effects meta-analyses for all factors reported by ≥2 studies.

Findings: Twenty-eight studies (23,963,716 patients) reported the association of 103 factors with opioid overdose after prescription for chronic pain. Moderate- to high-certainty evidence supported large associations with opioid overdose and a history of overdose (OR 5·85 [95% CI 3·78 to 9·04]), higher opioid dose (OR 2·57 [95% CI 2·08 to 3·18] for every 90-mg increment in daily morphine equivalent dose), ≥3 prescribers (OR 4·68 [95% CI 3·57 to 6·12]), ≥4 dispensing pharmacies (OR 4·92 [95% CI 4·35 to 5·57]), fentanyl (OR 2·80 [95% CI 2·30 to 3·41]), long-acting opioid formulations (OR 1·92 [95% CI 1·51 to 2·45]), current substance use disorder (OR 2·62 [95% CI 2·09 to 3·27]), any mental health diagnosis (OR 2·12 [95% CI 1·73 to 2·61]), depression (OR 2·22 [95% CI 1·57 to 3·14]), bipolar disorder (OR 2·07 [95% CI 1·77 to 2·41]), or pancreatitis (OR 2·00 [95% CI 1·52 to 2·64]). These factors were associated with absolute risks ranging from 2‰ to 6‰ for fatal and 4‰ to 12‰ for non-fatal overdose.

Interpretation: Minimizing high-dose opioid prescribing, fentanyl, long-acting formulations, multiple opioid prescribers or pharmacies, and opioid prescribing to chronic pain patients that have previously overdosed or present with a current substance use disorder, depression, bipolar disorder, or other mental illness, or pancreatitis may reduce the risk of opioid overdose when prescribed for chronic pain.

Funding: This study was supported by a grant from Health Canada. JWB is supported, in part, by a Canadian Institutes of Health Research Canada Research Chair in the prevention and management of chronic pain.

Declaration of Interest: All authors have completed the ICMJE uniform disclosure form and declare: no financial support from any industry for the submitted work.

Keywords: Opioids, Chronic Pain, Overdose, Death, Predictor, Meta-Analysis

Suggested Citation

Wang, Li and Hong, Patrick J. and Jiang, Wenjun and Rehman, Yasir and Hong, Brian Y. and Couban, Rachel J. and Wang, Chunming and Hayes, Corey and Juurlink, David N. and Busse, Jason W., Predictors of Fatal and Non-Fatal Overdose Following Prescription of Opioids for Chronic Pain: A Systematic Review and Meta-Analysis of Observational Studies. Available at SSRN: https://ssrn.com/abstract=4374583 or http://dx.doi.org/10.2139/ssrn.4374583

Li Wang (Contact Author)

McMaster University - Department of Anesthesia ( email )

Patrick J. Hong

University of Toronto - Department of Anesthesiology and Pain Medicine ( email )

Wenjun Jiang

McMaster University - Faculty of Health Sciences ( email )

Yasir Rehman

McMaster University - Michael G. DeGroote Institute for Pain Research and Care ( email )

Brian Y. Hong

University of Toronto - Division of Plastic Surgery ( email )

Rachel J. Couban

McMaster University - Michael G. DeGroote Institute for Pain Research and Care ( email )

Chunming Wang

Guangdong Academy of Sciences (GDAS) - Guangdong Science and Technology Library, and Institute of Information ( email )

Corey Hayes

University of Arkansas for Medical Sciences - Bioinformatics Program ( email )

David N. Juurlink

Queen's University - Institute for Clinical Evaluative Sciences ( email )

21 Arch Street
Kingston, Ontario K7L 3N6
Canada

Jason W. Busse

McMaster University - Department of Anesthesia ( email )